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Alternatives to animal models in diabetes research

Guest blog: Andrew Wilhelmsen, PhD student, FRAME Alternatives Laboratory, The University of Nottingham

Diabetes Week UK: 14 to 20 June 2021

In the UK today, there are 3.9 million people who have been diagnosed with diabetes and an estimated million more who are yet to be diagnosed [1]. That’s approximately 1 in 15 UK citizens living with diabetes. Type II diabetes (T2D) accounts for ~90% of diagnoses and is a condition whereby the pancreas produces some insulin, but its function is impaired and/or it is no longer produced in sufficient quantity. T2D is frequently associated with lifestyle factors such as diet, sedentariness and aging, which are commonly linked by obesity. Collectively, diabetes costs the NHS ~£10bn a year, or £1M per hour [2].

Skeletal muscle plays a vital role in maintaining blood glucose concentrations, as the major site of dietary glucose disposal in healthy individuals [3]. While human studies allow us to research a multitude of metabolic scenarios, some of the ‘basic’ elements – the how and why – can be confounded by other bodily systems, tissues and environmental factors. Animal studies can offer valuable insights, with levels of experimental control and degrees of risk that may not be tenable in human studies, however they can also present many issues. Fundamental differences between rodents and humans include muscle fibre type and composition [4], fat tissue type and distribution [5], biological ageing processes [6] and responses to diet [7] and exercise [8]. Furthermore, animal models of T2D are typically monogenic, that is to say that the condition is modelled through manipulation of a single gene (most frequently a deletion of the gene responsible for the hunger-satiating hormone leptin, which results in overfeeding, obesity and subsequent T2D), whereas human T2D is typically driven by a multitude of, and interaction between, environmental and genetic factors.

My research as a PhD student is focused on the development of insulin resistance in skeletal muscle (one of the first and most significant steps in the cascade that leads to T2D). My work covers a spectrum of approaches ‘from bench to bedside’ to try and paint a comprehensive picture of how and why insulin resistance occurs. My past and present research includes human exercise interventions, cross-sectional metabolic profiling and muscle-cell culture studies. The latter is where the FRAME Alternatives Laboratory comes in. To overcome some of the aforementioned challenges in ‘basic’ research, we use what is called human primary cell culture.

We recruit human volunteers and obtain tiny samples of muscle tissue, from which we can isolate dormant ‘satellite’ cells. Under favourable conditions, these cells can be stimulated and grown to ultimately form large, tubular, muscle cells (myotubes) that contain many of the fundamental components and properties of ‘real’ muscle fibres. We can condition these cells with nutrient mixtures that mimic the circulatory environment in obese or T2D individuals; stimulate them with electrical pulses to mimic exercise; or treat them with compounds to activate or inhibit biological processes. Remarkably, these cells retain a sort of memory of the donor’s muscle and will carry forward some distinguishable traits. Muscle cells cultured from obese T2D individuals, for instance, respond differently to ‘exercise’ and insulin stimulation than those from obese non-diabetic individuals [9, 10].

Advances in our understanding of whole-systems, muscle and cell biology are better enabling application of the 3Rs (Replacement, Reduction and Refinement of animals in experiments) to drive better research, better data and better patient outcomes. Indeed, thanks to more relevant cell culture models, modern drug design technology, and greater emphasis on well-designed human interventional studies, the tide is turning on the once-standard use of animals in many lines of scientific enquiry. Perhaps then, to misappropriate the words of the late great poet Alexander Pope; where possible ‘the proper study of mankind is man.’

For more information, visit the Diabetes UK website here. 


  1. NCVIN, Diabetes Prevalence Model for England + estimated growth between 2015–2020 from APHO (2010) Prevalence Models for Scotland and Wales. 2016.
  2. Hex, N., et al., Estimating the current and future costs of Type 1 and Type 2 diabetes in the UK, including direct health costs and indirect societal and productivity costs. Diabet Med, 2012. 29(7): p. 855-62.
  3. Abdul-Ghani, M.A. and R.A. DeFronzo, Pathogenesis of Insulin Resistance in Skeletal Muscle. Journal of Biomedicine and Biotechnology, 2010. 2010: p. 476279.
  4. Pette, D. and R.S. Staron, Cellular and molecular diversities of mammalian skeletal muscle fibers, in Reviews of Physiology, Biochemistry and Pharmacology, Volume 116: Volume: 116. 1990, Springer Berlin Heidelberg: Berlin, Heidelberg. p. 1-76.
  5. Zuriaga, M.A., et al., Humans and Mice Display Opposing Patterns of “Browning” Gene Expression in Visceral and Subcutaneous White Adipose Tissue Depots. Frontiers in Cardiovascular Medicine, 2017. 4(27).
  6. Welle, S., A. Brooks, and C.A. Thornton, Senescence-related changes in gene expression in muscle: similarities and differences between mice and men. Physiol Genomics, 2001. 5(2): p. 67-73.
  7. Lai, M., P.C. Chandrasekera, and N.D. Barnard, You are what you eat, or are you? The challenges of translating high-fat-fed rodents to human obesity and diabetes. Nutrition & diabetes, 2014. 4(9): p. e135-e135.
  8. Raun, S.H., et al., Housing temperature influences exercise training adaptations in mice. Nature Communications, 2020. 11(1): p. 1560.
  9. Feng, Y.Z., et al., Myotubes from lean and severely obese subjects with and without type 2 diabetes respond differently to an in vitro model of exercise. American Journal of Physiology-Cell Physiology, 2015. 308(7): p. C548-C556.
  10. Bakke, S.S., et al., Myotubes from severely obese type 2 diabetic subjects accumulate less lipids and show higher lipolytic rate than myotubes from severely obese non-diabetic subjects. PloS one, 2015. 10(3): p. e0119556-e0119556.
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